Photoacoustic computed tomography (PCT) is a rapidly emerging hybrid imaging modality that combines high ultrasonic resolution with strong optical or microwave contrast, and represents a highly promising biomedical imaging modality. While much effort has been devoted in recent years to developing image reconstruction theories and algorithms for PCT, a majority of these works have relied on the assumption of homogeneous acoustic properties such as the speed-of- sound and density. There remains a great need for the further development of accurate and robust image reconstruction methods that will facilitate the application of PCT to a variety of other important clinical imaging probles. In the proposed research, we will specifically develop and evaluate image reconstruction algorithms that will make PCT human brain imaging feasible. The development of PCT brain imaging methods would provide a means of monitoring brain conditions such as strokes, tumors, and brain injuries at the bedside or in the operating room, in near real-time, which is not feasible with X-ray CT or MRI. A major technical challenge is to develop effective image reconstruction algorithms that can compensate for the large differences in the acoustic properties of brain tissue and the skull. The broad objective of the proposed research is to develop and quantitatively evaluate innovative PCT image reconstruction methods that account for the imaging physics that is relevant to transskull brain imaging using PCT. Specifically, we will investigate the use of different imaging models that account for the effects of skull-induced wavefront aberrations and other physical factors to develop robust PCT reconstruction algorithms for brain imaging applications. The project will also establish an ideal research environment in which the candidate can acquire a rigorous training as a medical imaging scientist that will build upon his strong background in wave physics. The specific aims of the project are: (1) to develop ultrasound-based methods for determining skull geometry and acoustic properties; (2) to develop image reconstruction methods for PCT brain imaging that employ a priori knowledge of the acoustic properties of the skull to mitigate acoustic aberrations; and (3) to systematically assess image quality in computer-simulation studies and experimental studies of microwave-based PCT brain imaging.